SOTAVerified

Instruction Following

Instruction following is the basic task of the model. This task is dedicated to evaluating the ability of the large model to follow human instructions. It is hoped that the model can generate controllable and safe answers.

Papers

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Showing 341–350 of 1135 papers

TitleStatusHype
LHRS-Bot-Nova: Improved Multimodal Large Language Model for Remote Sensing Vision-Language InterpretationCode2
Zero-shot Object-Centric Instruction Following: Integrating Foundation Models with Traditional Navigation—0
LIFBench: Evaluating the Instruction Following Performance and Stability of Large Language Models in Long-Context ScenariosCode0
SetLexSem Challenge: Using Set Operations to Evaluate the Lexical and Semantic Robustness of Language ModelsCode1
Stronger Models are NOT Stronger Teachers for Instruction Tuning—0
MrSteve: Instruction-Following Agents in Minecraft with What-Where-When Memory—0
IOPO: Empowering LLMs with Complex Instruction Following via Input-Output Preference Optimization—0
Fox-1 Technical Report—0
Bayesian Calibration of Win Rate Estimation with LLM EvaluatorsCode0
Multi-Reward as Condition for Instruction-based Image Editing—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1AutoIF (Llama3 70B)Inst-level loose-accuracy90.4—Unverified
2AutoIF (Qwen2 72B)Inst-level loose-accuracy88—Unverified
3GPT-4Inst-level loose-accuracy85.37—Unverified
4PaLM 2 SInst-level loose-accuracy59.11—Unverified